An empirical validation of software cost estimation models
Communications of the ACM
Applied software measurement (2nd ed.): assuring productivity and quality
Applied software measurement (2nd ed.): assuring productivity and quality
COCOMO evaluation and tailoring
ICSE '85 Proceedings of the 8th international conference on Software engineering
Bayesian Analysis of Empirical Software Engineering Cost Models
IEEE Transactions on Software Engineering
Software Cost Estimation with Cocomo II with Cdrom
Software Cost Estimation with Cocomo II with Cdrom
Expert Systems: Principles and Programming
Expert Systems: Principles and Programming
COMPSAC '00 24th International Computer Software and Applications Conference
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Project management is one of the most critical activities in modern software development projects. Without realistic and objective management, the software development process cannot be managed in an effective way. However, diffi- culty in assessment of project attributes leads a project into failure. Therefore, it is essential to keep providing objective assessment of project attributes as software development evolves. Another important aspect of a software development project is to know how much it will cost. And predicting development effort is central to the project management. However, effort prediction is one of the most difficult tasks in project management. We use Bayesian approach to update productivity and predict effort based on the updated productivity. In this paper, we describe an extended tool that we added to PAMPA 2 (Project Attributes Monitoring and Prediction Associate) to help manage a project.